Visual representation expression based on player expression

ABSTRACT

Using facial recognition and gesture/body posture recognition techniques, a system can naturally convey the emotions and attitudes of a user via the user&#39;s visual representation. Techniques may comprise customizing a visual representation of a user based on detectable characteristics, deducting a user&#39;s temperament from the detectable characteristics, and applying attributes indicative of the temperament to the visual representation in real time. Techniques may also comprise processing changes to the user&#39;s characteristics in the physical space and updating the visual representation in real time. For example, the system may track a user&#39;s facial expressions and body movements to identify a temperament and then apply attributes indicative of that temperament to the visual representation. Thus, a visual representation of a user, such as an avatar or fanciful character, can reflect the user&#39;s expressions and moods in real time.

BACKGROUND

Often, various applications will display a visual representation thatcorresponds to a user that the user controls through certain actions,such as selecting buttons on a remote or moving a controller in acertain manner. The visual representation may be in the form of anavatar, a fanciful character, a cartoon image or animal, a cursor, ahand, or the like. The visual representation is a computerrepresentation corresponding to a user that typically takes the form ofa two-dimensional (2D) or three-dimensional (3D) model in variousapplications, such as computer games, video games, chats, forums,communities, instant messaging services, and the like. Many computingapplications such as computer games, multimedia applications, officeapplications, or the like provide a selection of predefined animatedcharacters that may be selected for use in the application as the user'savatar. Some systems may incorporate a camera that has the ability totake a picture of a user and identify features from that frame of data.However, these systems require a capture of a user's feature, processingof the image, and then application to the character in a non-real timeenvironment, and the features applied are low fidelity, usually based ona single snapshot of the user.

SUMMARY

It may be desirable to customize a visual representation of a user basedon the detected characteristics of the user and it may be desirable toapply the characteristics to the visual representation in real time. Itmay also be desirable that the system processes changes to the user'scharacteristics in the physical space and can update the visualrepresentation in real time. Of these characteristics, it may bedesirable that the system identifies a user's temperament and appliesattributes indicative of the temperament to the user's visualrepresentation.

Disclosed herein are techniques for providing a visual representation ofa user, such as an avatar or fanciful character, that can reflect theuser's temperament in real time. Using facial recognition andgesture/body posture recognition techniques, the system can deduct auser's temperament. The system can naturally convey the emotions andattitudes of a user via the application of attributes of the user'stemperament to the user's visual representation. Also disclosed aretechniques for tracking the user in the physical space over time andapplying modifications or updates to the visual representation in realtime. For example, the system may track a user's facial expressions andbody movements to identify a temperament and then apply attributesindicative of that temperament to the visual representation. The systemmay use any detectable characteristics to evaluate the user'stemperament for application to the visual representation.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Furthermore,the claimed subject matter is not limited to implementations that solveany or all disadvantages noted in any part of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The systems, methods, and computer readable media for modifying a visualrepresentation in accordance with this specification are furtherdescribed with reference to the accompanying drawings in which:

FIG. 1 illustrates an example embodiment of a target recognition,analysis, and tracking system with a user playing a game.

FIG. 2 illustrates an example embodiment of a capture device that may beused in a target recognition, analysis, and tracking system andincorporate chaining and animation blending techniques.

FIG. 3 illustrates an example embodiment of a computing environment inwhich the animation techniques described herein may be embodied.

FIG. 4 illustrates another example embodiment of a computing environmentin which the animation techniques described herein may be embodied.

FIG. 5A illustrates a skeletal mapping of a user that has been generatedfrom a depth image.

FIG. 5B illustrates further details of the gesture recognizerarchitecture shown in FIG. 2.

FIG. 6 depicts an example target recognition, analysis, and trackingsystem and an example embodiment of a user in the physical space and adisplay of the user's visual representation.

FIG. 7 depicts an example flow diagram for a method of applyingattributes indicative of a user's temperament to a visualrepresentation.

FIG. 8 depicts an example lookup table for deducing a user'stemperament.

FIG. 9 depicts another example target recognition, analysis, andtracking system and example embodiments of the user in the physicalspace and example embodiments of the display of the user's visualrepresentation.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Disclosed herein are techniques for providing a visual representation ofa user, such as an avatar, that can reflect the user's temperament. Thevisual representation of the user may be in the form of a character, ananimation, an avatar, a cursor on the screen, a hand, or any othervirtual representation that corresponds to the user in the physicalspace. Using facial recognition and gesture/body posture recognitiontechniques, a system can naturally convey the emotions and attitudes ofa user via the user's visual representation. For example, a capturedevice may identify features of a user and customize the user's visualrepresentation based on those identified features, such as emotions,expressions, and moods. In an example embodiment, the system generatesand uses aspects of a skeletal or mesh model of a person based on theimage data captured by the capture device, and uses body recognitiontechniques to determine the user's temperament.

Also disclosed are techniques for displaying the visual representationin real time and applying attributes indicative of a user's temperamentto the visual representation in real time. The system may track the userin the physical space over time and apply modifications or updates tothe visual representation in real time. The system may track detectablecharacteristics such as a user's characteristics, gestures, anapplication status, etc., to deduce a user's temperament. A user'scharacteristics, for example, such as facial expressions and bodymovements, may be used to deduce a temperament and then attributes ofthat temperament may be applied to the visual representation so that thevisual representation reflects the user's temperament. For example, thecapture device may identify behaviors and mannerisms, emotions, speechpatterns, history data, or the like, of a user to determine the user'stemperament and apply these to the user's visual representation. Thesystem may use any detectable features to evaluate the user'stemperament for application to the visual representation.

To generate a model representative of a target or object in a physicalspace, a capture device can capture a depth image of the scene and scantargets or objects in the scene. A target may be a human target, such asa user, in the physical space. Thus, as used herein, it is understoodthat target and user may be used interchangeably. In one embodiment, thecapture device may determine whether one or more targets or objects inthe scene correspond to a human target such as the user. To determinewhether a target or object in the scene corresponds a human target, eachof the targets may be flood filled and compared to a pattern of a humanbody model. Each target or object that matches the human body model maythen be scanned to generate a skeletal model associated therewith. Forexample, a target identified as a human may be scanned to generate askeletal model associated therewith. The skeletal model may then beprovided to the computing environment for tracking the skeletal modeland rendering a visual representation associated with the skeletalmodel. The computing environment may determine which controls to performin an application executing on the computer environment based on, forexample, gestures of the user that have been recognized and mapped tothe skeletal model. Thus, user feedback may be displayed, such as via anavatar on a screen, and the user can control that avatar's motion bymaking gestures in the physical space.

The motion of the visual representation can be controlled by mapping themovement of the visual representation to the motion of the user in thephysical space. For example, the target may be a human user that ismotioning or gesturing in the physical space. The visual representationof the target may be an avatar displayed on a screen, and the avatar'smotion may correspond to the user's motion. Motion in the physical spacemay be translated to a control in a system or application space, such asa virtual space and/or a game space. For example, a user's motions maybe tracked, modeled, and displayed, and the user's gestures may controlcertain aspects of an operating system or executing application. Theuser's gestures may be translated to a control in the system orapplication space for applying attributes indicative of a temperament toa visual representation.

Captured motion may be any motion in the physical space that is capturedby the capture device, such as a camera. The captured motion couldinclude the motion of a target in the physical space, such as a user oran object. The captured motion may include a gesture that translates toa control in an operating system or application. The motion may bedynamic, such as a running motion, or the motion may be static, such asa user that is posed with little movement.

The system, methods, and components of facial and body recognition forconveying a user's attitudes and emotions described herein may beembodied in a multi-media console, such as a gaming console, or in anyother computing device in which it is desired to display a visualrepresentation of a target, including, by way of example and without anyintended limitation, satellite receivers, set top boxes, arcade games,personal computers (PCs), portable telephones, personal digitalassistants (PDAs), and other hand-held devices.

FIG. 1 illustrates an example embodiment of a configuration of a targetrecognition, analysis, and tracking system 10 that may employ techniquesfor applying characteristics of the user to a visual representation. Inthe example embodiment, a user 18 is playing a boxing game. In anexample embodiment, the system 10 may recognize, analyze, and/or track ahuman target such as the user 18. The system 10 may gather informationrelated to the user's motions, facial expressions, body language,emotions, etc., in the physical space. For example, the system mayidentify and scan the human target 18. The system 10 may use bodyposture recognition techniques to identify the temperament of the humantarget 18. For example, if the user 18 slouches, folds his hands overhis chest, and motions his head to the side with lethargic motion, thesystem 10 may identify the body parts of the user 18 and how they move.The system 10 may compare the motions to a library of emotions, moods,attitudes, expressions, etc., to interpret the temperament of the user.

As shown in FIG. 1, the target recognition, analysis, and trackingsystem 10 may include a computing environment 12. The computingenvironment 12 may be a computer, a gaming system or console, or thelike. According to an example embodiment, the computing environment 12may include hardware components and/or software components such that thecomputing environment 12 may be used to execute applications such asgaming applications, non-gaming applications, or the like.

As shown in FIG. 1, the target recognition, analysis, and trackingsystem 10 may further include a capture device 20. The capture device 20may be, for example, a camera that may be used to visually monitor oneor more users, such as the user 18, such that gestures performed by theone or more users may be captured, analyzed, and tracked to perform oneor more controls or actions within an application, as will be describedin more detail below.

According to one embodiment, the target recognition, analysis, andtracking system 10 may be connected to an audiovisual device 16 such asa television, a monitor, a high-definition television (HDTV), or thelike that may provide game or application visuals and/or audio to a usersuch as the user 18. For example, the computing environment 12 mayinclude a video adapter such as a graphics card and/or an audio adaptersuch as a sound card that may provide audiovisual signals associatedwith the game application, non-game application, or the like. Theaudiovisual device 16 may receive the audiovisual signals from thecomputing environment 12 and may then output the game or applicationvisuals and/or audio associated with the audiovisual signals to the user18. According to one embodiment, the audiovisual device 16 may beconnected to the computing environment 12 via, for example, an S-Videocable, a coaxial cable, an HDMI cable, a DVI cable, a VGA cable, or thelike.

As shown in FIG. 1, the target recognition, analysis, and trackingsystem 10 may be used to recognize, analyze, and/or track a human targetsuch as the user 18. For example, the user 18 may be tracked using thecapture device 20 such that the movements of user 18 may be interpretedas controls that may be used to affect the application being executed bycomputer environment 12. Thus, according to one embodiment, the user 18may move his or her body to control the application. The system 10 maytrack the user's body and the motions made by the user's body, includinggestures that control aspects of the system, such as the application,operating system, or the like. The system may compare the user's bodyposture, facial expressions, vocal expressions and tone, directed gazes,etc., to determine a user's temperament or attitude and applycharacteristics of that temperament or attitude to the avatar.

The system 10 may translate an input to a capture device 20 into ananimation, the input being representative of a user's motion, such thatthe animation is driven by that input. Thus, the user's motions may mapto a visual representation 40 such that the user's motions in thephysical space are performed by the avatar 40. The user's motions may begestures that are applicable to a control in an application. As shown inFIG. 1, in an example embodiment, the application executing on thecomputing environment 12 may be a boxing game that the user 18 may beplaying.

The computing environment 12 may use the audiovisual device 16 toprovide a visual representation of a player avatar 40 that the user 18may control with his or her movements. For example, the user 18 maythrow a punch in physical space to cause the player avatar 40 to throw apunch in game space. The player avatar 40 may have the characteristicsof the user identified by the capture device 20, or the system 10 mayuse the features of a well-known boxer or portray the physique of aprofessional boxer for the visual representation that maps to the user'smotions. The system 10 may track the user and modify characteristics ofthe user's avatar based on detectable features of the user in thephysical space. The computing environment 12 may also use theaudiovisual device 16 to provide a visual representation of a boxingopponent 38 to the user 18. According to an example embodiment, thecomputer environment 12 and the capture device 20 of the targetrecognition, analysis, and tracking system 10 may be used to recognizeand analyze the punch of the user 18 in the physical space such that thepunch may be interpreted as a game control of the player avatar 40 ingame space. Multiple users can interact with each other from remotelocations. For example, the visual representation of the boxing opponent38 may be representative of another user, such as a second user in thephysical space with user 18 or a networked user in a second physicalspace.

Other movements by the user 18 may also be interpreted as other controlsor actions, such as controls to bob, weave, shuffle, block, jab, orthrow a variety of different power punches. Furthermore, some movementsmay be interpreted as controls that may correspond to actions other thancontrolling the player avatar 40. For example, the player may usemovements to end, pause, or save a game, select a level, view highscores, communicate with a friend, etc. Additionally, a full range ofmotion of the user 18 may be available, used, and analyzed in anysuitable manner to interact with an application.

In example embodiments, the human target such as the user 18 may have anobject. In such embodiments, the user of an electronic game may beholding the object such that the motions of the player and the objectmay be used to adjust and/or control parameters of the game. Forexample, the motion of a player holding a racket may be tracked andutilized for controlling an on-screen racket in an electronic sportsgame. In another example embodiment, the motion of a player holding anobject may be tracked and utilized for controlling an on-screen weaponin an electronic combat game.

A user's gestures or motion may be interpreted as controls that maycorrespond to actions other than controlling the player avatar 40. Forexample, the player may use movements to end, pause, or save a game,select a level, view high scores, communicate with a friend, etc. Theplayer may use movements to apply attributes indicative of a temperamentto the user's visual representation. Virtually any controllable aspectof an operating system and/or application may be controlled by movementsof the target such as the user 18. According to other exampleembodiments, the target recognition, analysis, and tracking system 10may interpret target movements for controlling aspects of an operatingsystem and/or application that are outside the realm of games.

An application of a user's feature to a visual representation or thedetection of certain emotions or attitudes of the user may be an aspectof the operating system and/or application that can be controlled by orrecognized from the user's gestures. For example, a gesture for a user'shands folded across his or her chest may be a gesture recognized as amood of frustration. The system's recognition of a gesture thatindicates the user is frustrated, along with a user's expression, suchas a frown, may result in a visual representation that reflects afrustrated temperament.

The user's gesture may be controls applicable to an operating system,non-gaming aspects of a game, or a non-gaming application. The user'sgestures may be interpreted as object manipulation, such as controllinga user interface. For example, consider a user interface having bladesor a tabbed interface lined up vertically left to right, where theselection of each blade or tab opens up the options for various controlswithin the application or the system. The system may identify the user'shand gesture for movement of a tab, where the user's hand in thephysical space is virtually aligned with a tab in the application space.The gesture, including a pause, a grabbing motion, and then a sweep ofthe hand to the left, may be interpreted as the selection of a tab, andthen moving it out of the way to open the next tab.

FIG. 2 illustrates an example embodiment of a capture device 20 that maybe used for target recognition, analysis, and tracking, where the targetcan be a user or an object. According to an example embodiment, thecapture device 20 may be configured to capture video with depthinformation including a depth image that may include depth values viaany suitable technique including, for example, time-of-flight,structured light, stereo image, or the like. According to oneembodiment, the capture device 20 may organize the calculated depthinformation into “Z layers,” or layers that may be perpendicular to a Zaxis extending from the depth camera along its line of sight.

As shown in FIG. 2, the capture device 20 may include an image cameracomponent 22. According to an example embodiment, the image cameracomponent 22 may be a depth camera that may capture the depth image of ascene. The depth image may include a two-dimensional (2-D) pixel area ofthe captured scene where each pixel in the 2-D pixel area may representa depth value such as a length or distance in, for example, centimeters,millimeters, or the like of an object in the captured scene from thecamera.

As shown in FIG. 2, according to an example embodiment, the image cameracomponent 22 may include an IR light component 24, a three-dimensional(3-D) camera 26, and an RGB camera 28 that may be used to capture thedepth image of a scene. For example, in time-of-flight analysis, the IRlight component 24 of the capture device 20 may emit an infrared lightonto the scene and may then use sensors (not shown) to detect thebackscattered light from the surface of one or more targets and objectsin the scene using, for example, the 3-D camera 26 and/or the RGB camera28. In some embodiments, pulsed infrared light may be used such that thetime between an outgoing light pulse and a corresponding incoming lightpulse may be measured and used to determine a physical distance from thecapture device 20 to a particular location on the targets or objects inthe scene. Additionally, in other example embodiments, the phase of theoutgoing light wave may be compared to the phase of the incoming lightwave to determine a phase shift. The phase shift may then be used todetermine a physical distance from the capture device 20 to a particularlocation on the targets or objects.

According to another example embodiment, time-of-flight analysis may beused to indirectly determine a physical distance from the capture device20 to a particular location on the targets or objects by analyzing theintensity of the reflected beam of light over time via varioustechniques including, for example, shuttered light pulse imaging.

In another example embodiment, the capture device 20 may use astructured light to capture depth information. In such an analysis,patterned light (i.e., light displayed as a known pattern such as gridpattern or a stripe pattern) may be projected onto the scene via, forexample, the IR light component 24. Upon striking the surface of one ormore targets or objects in the scene, the pattern may become deformed inresponse. Such a deformation of the pattern may be captured by, forexample, the 3-D camera 26 and/or the RGB camera 28 and may then beanalyzed to determine a physical distance from the capture device 20 toa particular location on the targets or objects.

According to another embodiment, the capture device 20 may include twoor more physically separated cameras that may view a scene fromdifferent angles, to obtain visual stereo data that may be resolved togenerate depth information

The capture device 20 may further include a microphone 30, or an arrayof microphones. The microphone 30 may include a transducer or sensorthat may receive and convert sound into an electrical signal. Accordingto one embodiment, the microphone 30 may be used to reduce feedbackbetween the capture device 20 and the computing environment 12 in thetarget recognition, analysis, and tracking system 10. Additionally, themicrophone 30 may be used to receive audio signals that may also beprovided by the user to control applications such as game applications,non-game applications, or the like that may be executed by the computingenvironment 12.

In an example embodiment, the capture device 20 may further include aprocessor 32 that may be in operative communication with the imagecamera component 22. The processor 32 may include a standardizedprocessor, a specialized processor, a microprocessor, or the like thatmay execute instructions that may include instructions for receiving thedepth image, determining whether a suitable target may be included inthe depth image, converting the suitable target into a skeletalrepresentation or model of the target, or any other suitableinstruction.

The capture device 20 may further include a memory component 34 that maystore the instructions that may be executed by the processor 32, imagesor frames of images captured by the 3-d camera 26 or RGB camera 28, orany other suitable information, images, or the like. According to anexample embodiment, the memory component 34 may include random accessmemory (RAM), read only memory (ROM), cache, Flash memory, a hard disk,or any other suitable storage component. As shown in FIG. 2, in oneembodiment, the memory component 34 may be a separate component incommunication with the image capture component 22 and the processor 32.According to another embodiment, the memory component 34 may beintegrated into the processor 32 and/or the image capture component 22.

As shown in FIG. 2, the capture device 20 may be in communication withthe computing environment 12 via a communication link 36. Thecommunication link 36 may be a wired connection including, for example,a USB connection, a Firewire connection, an Ethernet cable connection,or the like and/or a wireless connection such as a wireless 802.11b, g,a, or n connection. According to one embodiment, the computingenvironment 12 may provide a clock to the capture device 20 that may beused to determine when to capture, for example, a scene via thecommunication link 36.

Additionally, the capture device 20 may provide the depth informationand images captured by, for example, the 3-D camera 26 and/or the RGBcamera 28, and a skeletal model that may be generated by the capturedevice 20 to the computing environment 12 via the communication link 36.The computing environment 12 may then use the skeletal model, depthinformation, and captured images to, for example, control an applicationsuch as a game or word processor. For example, as shown, in FIG. 2, thecomputing environment 12 may include a gestures library 190.

As shown, in FIG. 2, the computing environment 12 may include a gestureslibrary 190 and a gestures recognition engine 192. The gesturesrecognition engine 192 may include a collection of gesture filters 191.A filter may comprise code and associated data that can recognizegestures or otherwise process depth, RGB, or skeletal data. Each filter191 may comprise information defining a gesture along with parameters,or metadata, for that gesture. For instance, a throw, which comprisesmotion of one of the hands from behind the rear of the body to past thefront of the body, may be implemented as a gesture filter 191 comprisinginformation representing the movement of one of the hands of the userfrom behind the rear of the body to past the front of the body, as thatmovement would be captured by a depth camera. Parameters may then be setfor that gesture. Where the gesture is a throw, a parameter may be athreshold velocity that the hand has to reach, a distance the hand musttravel (either absolute, or relative to the size of the user as awhole), and a confidence rating by the recognizer engine that thegesture occurred. These parameters for the gesture may vary betweenapplications, between contexts of a single application, or within onecontext of one application over time.

While it is contemplated that the gestures recognition engine mayinclude a collection of gesture filters, where a filter may comprisecode or otherwise represent a component for processing depth, RGB, orskeletal data, the use of a filter is not intended to limit the analysisto a filter. The filter is a representation of an example component orsection of code that analyzes data of a scene received by a system, andcomparing that data to base information that represents a gesture. As aresult of the analysis, the system may produce an output correspondingto whether the input data corresponds to the gesture. The baseinformation representing the gesture may be adjusted to correspond tothe recurring feature in the history of data representative of theuser's capture motion. The base information, for example, may be part ofa gesture filter as described above. But, any suitable manner foranalyzing the input data and gesture data is contemplated.

A gesture may be recognized as a temperament identity gesture. In anexample embodiment, the motion in the physical space may berepresentative of a gesture recognized as a request to apply attributesof a particular temperament to the visual representation of a target. Aplurality of gestures may each represent a particular temperamentidentity gesture. Thus, a user can control the form of the visualrepresentation by making a gesture in the physical space that isrecognized as a temperament identity gesture. For example, as describedabove, the user's motion may be compared to a gesture filter, such asgesture filter 191 from FIG. 2. The gesture filter 191 may compriseinformation for a temperament identity gesture from the temperamentidentity gestures 196 in the gestures library 190.

A plurality of temperament identity gestures may each represent atemperament having attributes to be applied to a visual representationon the screen. For example, an “excited” identify gesture may berecognized from the identity of a user's motion comprising a jumping upand down motion with the user's arms raised in the air. The result maybe the application of attributes, directly mapped to the user's motionand/or animations in addition to the user's motion, to the user's visualrepresentation.

The data captured by the cameras 26, 28 and device 20 in the form of theskeletal model and movements associated with it may be compared to thegesture filters 191 in the gesture library 190 to identify when a user(as represented by the skeletal model) has performed one or moregestures. Thus, inputs to a filter such as filter 191 may comprisethings such as joint data about a user's joint position, like anglesformed by the bones that meet at the joint, RGB color data from thescene, and the rate of change of an aspect of the user. As mentioned,parameters may be set for the gesture. Outputs from a filter 191 maycomprise things such as the confidence that a given gesture is beingmade, the speed at which a gesture motion is made, and a time at whichthe gesture occurs.

The computing environment 12 may include a processor 195 that canprocess the depth image to determine what targets are in a scene, suchas a user 18 or an object in the room. This can be done, for instance,by grouping together of pixels of the depth image that share a similardistance value. The image may also be parsed to produce a skeletalrepresentation of the user, where features, such as joints and tissuesthat run between joints are identified. There exist skeletal mappingtechniques to capture a person with a depth camera and from thatdetermine various spots on that user's skeleton, joints of the hand,wrists, elbows, knees, nose, ankles, shoulders, and where the pelvismeets the spine. Other techniques include transforming the image into abody model representation of the person and transforming the image intoa mesh model representation of the person.

In an embodiment, the processing is performed on the capture device 20itself, and the raw image data of depth and color (where the capturedevice 20 comprises a 3D camera 26) values are transmitted to thecomputing environment 12 via link 36. In another embodiment, theprocessing is performed by a processor 32 coupled to the camera 402 andthen the parsed image data is sent to the computing environment 12. Instill another embodiment, both the raw image data and the parsed imagedata are sent to the computing environment 12. The computing environment12 may receive the parsed image data but it may still receive the rawdata for executing the current process or application. For instance, ifan image of the scene is transmitted across a computer network toanother user, the computing environment 12 may transmit the raw data forprocessing by another computing environment.

The computing environment 12 may use the gestures library 190 tointerpret movements of the skeletal model and to control an applicationbased on the movements. The computing environment 12 can model anddisplay a representation of a user, such as in the form of an avatar ora pointer on a display, such as in a display device 193. Display device193 may include a computer monitor, a television screen, or any suitabledisplay device. For example, a camera-controlled computer system maycapture user image data and display user feedback on a television screenthat maps to the user's gestures. The user feedback may be displayed asan avatar on the screen such as shown in FIGS. 1A and 1B. The avatar'smotion can be controlled directly by mapping the avatar's movement tothose of the user's movements. The user's gestures may be interpretedcontrol certain aspects of the application.

As described above, it may be desirable to apply attributes of atemperament to a target's visual representation. For example, a user maywish to make the user's visual representation do a dance on the screento indicate the user's happiness. The user may initiate the applicationof such attributes by performing a particular temperament identitygesture.

According to an example embodiment, the target may be a human target inany position such as standing or sitting, a human target with an object,two or more human targets, one or more appendages of one or more humantargets or the like that may be scanned, tracked, modeled and/orevaluated to generate a virtual screen, compare the user to one or morestored profiles and/or to store profile information 198 about the targetin a computing environment such as computing environment 12. The profileinformation 198 may be in the form of user profiles, personal profiles,application profiles, system profiles, or any other suitable method forstoring data for later access. The profile information 198 may beaccessible via an application or be available system-wide, for example.The profile information 198 may include lookup tables for loadingspecific user profile information. The virtual screen may interact withan application that may be executed by the computing environment 12described above with respect to FIGS. 1A-1B.

According to example embodiments, lookup tables may include userspecific profile information. In one embodiment, the computingenvironment such as computing environment 12 may include stored profiledata 198 about one or more users in lookup tables. The stored profiledata 198 may include, among other things the targets scanned orestimated body size, skeletal models, body models, voice samples orpasswords, the targets age, previous gestures, target limitations andstandard usage by the target of the system, such as, for example atendency to sit, left or right handedness, or a tendency to stand verynear the capture device. This information may be used to determine ifthere is a match between a target in a capture scene and one or moreuser profiles 198 that, in one embodiment, may allow the system to adaptthe virtual screen to the user, or to adapt other elements of thecomputing or gaming experience according to the profile 198.

One or more personal profiles 198 may be stored in computer environment12 and used in a number of user sessions, or one or more personalprofiles may be created for a single session only. Users may have theoption of establishing a profile where they may provide information tothe system such as a voice or body scan, age, personal preferences,right or left handedness, an avatar, a name or the like. Personalprofiles may also be provided for “guests” who do not provide anyinformation to the system beyond stepping into the capture space. Atemporary personal profile may be established for one or more guests. Atthe end of a guest session, the guest personal profile may be stored ordeleted.

The gestures library 190, gestures recognition engine 192, and profile198 may be implemented in hardware, software or a combination of both.For example, the gestures library 190, and gestures recognition engine192 may be implemented as software that executes on a processor, such asprocessor 195, of the computing environment 12 (or on processing unit101 of FIG. 3 or processing unit 259 of FIG. 4).

It is emphasized that the block diagram depicted in FIGS. 2 and FIGS.3-4 described below are exemplary and not intended to imply a specificimplementation. Thus, the processor 195 or 32 in FIG. 1, the processingunit 101 of FIG. 3, and the processing unit 259 of FIG. 4, can beimplemented as a single processor or multiple processors. Multipleprocessors can be distributed or centrally located. For example, thegestures library 190 may be implemented as software that executes on theprocessor 32 of the capture device or it may be implemented as softwarethat executes on the processor 195 in the computing environment 12. Anycombinations of processors that are suitable for performing thetechniques disclosed herein are contemplated. Multiple processors cancommunicate wirelessly, via hard wire, or a combination thereof.

Furthermore, as used herein, a computing environment 12 may refer to asingle computing device or to a computing system. The computingenvironment may include non-computing components. The computingenvironment may include a display device, such as display device 193shown in FIG. 2. A display device may be an entity separate but coupledto the computing environment or the display device may be the computingdevice that processes and displays, for example. Thus, a computingsystem, computing device, computing environment, computer, processor, orother computing component may be used interchangeably.

The gestures library and filter parameters may be tuned for anapplication or a context of an application by a gesture tool. A contextmay be a cultural context, and it may be an environmental context. Acultural context refers to the culture of a user using a system.Different cultures may use similar gestures to impart markedly differentmeanings. For instance, an American user who wishes to tell another userto “look” or “use his eyes” may put his index finger on his head closeto the distal side of his eye. However, to an Italian user, this gesturemay be interpreted as a reference to the mafia.

Similarly, there may be different contexts among different environmentsof a single application. Take a first-user shooter game that involvesoperating a motor vehicle. While the user is on foot, making a firstwith the fingers towards the ground and extending the first in front andaway from the body may represent a punching gesture. While the user isin the driving context, that same motion may represent a “gear shifting”gesture. With respect to modifications to the visual representation,different gestures may trigger different modifications depending on theenvironment. A different modification trigger gesture could be used forentry into an application-specific modification mode versus asystem-wide modification mode. Each modification mode may be packagedwith an independent set of gestures that correspond to the modificationmode, entered into as a result of the modification trigger gesture. Forexample, in a bowling game, a swinging arm motion may be a gestureidentified as swinging a bowling ball for release down a virtual bowlingalley. However, in another application, the swinging arm motion may be agesture identified as a request to lengthen the arm of the user's avatardisplayed on the screen. There may also be one or more menuenvironments, where the user can save his game, select among hischaracter's equipment or perform similar actions that do not comprisedirect game-play. In that environment, this same gesture may have athird meaning, such as to select something or to advance to anotherscreen.

Gestures may be grouped together into genre packages of complimentarygestures that are likely to be used by an application in that genre.Complimentary gestures—either complimentary as in those that arecommonly used together, or complimentary as in a change in a parameterof one will change a parameter of another—may be grouped together intogenre packages. These packages may be provided to an application, whichmay select at least one. The application may tune, or modify, theparameter of a gesture or gesture filter 191 to best fit the uniqueaspects of the application. When that parameter is tuned, a second,complimentary parameter (in the inter-dependent sense) of either thegesture or a second gesture is also tuned such that the parametersremain complimentary. Genre packages for video games may include genressuch as first-user shooter, action, driving, and sports.

FIG. 3 illustrates an example embodiment of a computing environment thatmay be used to interpret one or more gestures in target recognition,analysis, and tracking system. The computing environment such as thecomputing environment 12 described above with respect to FIGS. 1A-2 maybe a multimedia console 100, such as a gaming console. As shown in FIG.3, the multimedia console 100 has a central processing unit (CPU) 101having a level 1 cache 102, a level 2 cache 104, and a flash ROM (ReadOnly Memory) 106. The level 1 cache 102 and a level 2 cache 104temporarily store data and hence reduce the number of memory accesscycles, thereby improving processing speed and throughput. The CPU 101may be provided having more than one core, and thus, additional level 1and level 2 caches 102 and 104. The flash ROM 106 may store executablecode that is loaded during an initial phase of a boot process when themultimedia console 100 is powered ON.

A graphics processing unit (GPU) 108 and a video encoder/video codec(coder/decoder) 114 form a video processing pipeline for high speed andhigh resolution graphics processing. Data is carried from the graphicsprocessing unit 108 to the video encoder/video codec 114 via a bus. Thevideo processing pipeline outputs data to an A/V (audio/video) port 140for transmission to a television or other display. A memory controller110 is connected to the GPU 108 to facilitate processor access tovarious types of memory 112, such as, but not limited to, a RAM (RandomAccess Memory).

The multimedia console 100 includes an I/O controller 120, a systemmanagement controller 122, an audio processing unit 123, a networkinterface controller 124, a first USB host controller 126, a second USBcontroller 128 and a front panel I/O subassembly 130 that are preferablyimplemented on a module 118. The USB controllers 126 and 128 serve ashosts for peripheral controllers 142(1)-142(2), a wireless adapter 148,and an external memory device 146 (e.g., flash memory, external CD/DVDROM drive, removable media, etc.). The network interface 124 and/orwireless adapter 148 provide access to a network (e.g., the Internet,home network, etc.) and may be any of a wide variety of various wired orwireless adapter components including an Ethernet card, a modem, aBluetooth module, a cable modem, and the like.

System memory 143 is provided to store application data that is loadedduring the boot process. A media drive 144 is provided and may comprisea DVD/CD drive, hard drive, or other removable media drive, etc. Themedia drive 144 may be internal or external to the multimedia console100. Application data may be accessed via the media drive 144 forexecution, playback, etc. by the multimedia console 100. The media drive144 is connected to the I/O controller 120 via a bus, such as a SerialATA bus or other high speed connection (e.g., IEEE 1394).

The system management controller 122 provides a variety of servicefunctions related to assuring availability of the multimedia console100. The audio processing unit 123 and an audio codec 132 form acorresponding audio processing pipeline with high fidelity and stereoprocessing. Audio data is carried between the audio processing unit 123and the audio codec 132 via a communication link. The audio processingpipeline outputs data to the A/V port 140 for reproduction by anexternal audio player or device having audio capabilities.

The front panel I/O subassembly 130 supports the functionality of thepower button 150 and the eject button 152, as well as any LEDs (lightemitting diodes) or other indicators exposed on the outer surface of themultimedia console 100. A system power supply module 136 provides powerto the components of the multimedia console 100. A fan 138 cools thecircuitry within the multimedia console 100.

The CPU 101, GPU 108, memory controller 110, and various othercomponents within the multimedia console 100 are interconnected via oneor more buses, including serial and parallel buses, a memory bus, aperipheral bus, and a processor or local bus using any of a variety ofbus architectures. By way of example, such architectures can include aPeripheral Component Interconnects (PCI) bus, PCI-Express bus, etc.

When the multimedia console 100 is powered ON, application data may beloaded from the system memory 143 into memory 112 and/or caches 102, 104and executed on the CPU 101. The application may present a graphicaluser interface that provides a consistent user experience whennavigating to different media types available on the multimedia console100. In operation, applications and/or other media contained within themedia drive 144 may be launched or played from the media drive 144 toprovide additional functionalities to the multimedia console 100.

The multimedia console 100 may be operated as a standalone system bysimply connecting the system to a television or other display. In thisstandalone mode, the multimedia console 100 allows one or more users tointeract with the system, watch movies, or listen to music. However,with the integration of broadband connectivity made available throughthe network interface 124 or the wireless adapter 148, the multimediaconsole 100 may further be operated as a participant in a larger networkcommunity.

When the multimedia console 100 is powered ON, a set amount of hardwareresources are reserved for system use by the multimedia consoleoperating system. These resources may include a reservation of memory(e.g., 16 MB), CPU and GPU cycles (e.g., 5%), networking bandwidth(e.g., 8 kbs.), etc. Because these resources are reserved at system boottime, the reserved resources do not exist from the application's view.

In particular, the memory reservation preferably is large enough tocontain the launch kernel, concurrent system applications and drivers.The CPU reservation is preferably constant such that if the reserved CPUusage is not used by the system applications, an idle thread willconsume any unused cycles.

With regard to the GPU reservation, lightweight messages generated bythe system applications (e.g., pop-ups) are displayed by using a GPUinterrupt to schedule code to render popup into an overlay. The amountof memory required for an overlay depends on the overlay area size andthe overlay preferably scales with screen resolution. Where a full userinterface is used by the concurrent system application, it is preferableto use a resolution independent of application resolution. A scaler maybe used to set this resolution such that the need to change frequencyand cause a TV resynch is eliminated.

After the multimedia console 100 boots and system resources arereserved, concurrent system applications execute to provide systemfunctionalities. The system functionalities are encapsulated in a set ofsystem applications that execute within the reserved system resourcesdescribed above. The operating system kernel identifies threads that aresystem application threads versus gaming application threads. The systemapplications are preferably scheduled to run on the CPU 101 atpredetermined times and intervals in order to provide a consistentsystem resource view to the application. The scheduling is to minimizecache disruption for the gaming application running on the console.

When a concurrent system application requires audio, audio processing isscheduled asynchronously to the gaming application due to timesensitivity. A multimedia console application manager (described below)controls the gaming application audio level (e.g., mute, attenuate) whensystem applications are active.

Input devices (e.g., controllers 142(1) and 142(2)) are shared by gamingapplications and system applications. The input devices are not reservedresources, but are to be switched between system applications and thegaming application such that each will have a focus of the device. Theapplication manager preferably controls the switching of input stream,without knowledge the gaming application's knowledge and a drivermaintains state information regarding focus switches. The cameras 26, 28and capture device 20 may define additional input devices for theconsole 100.

FIG. 4 illustrates another example embodiment of a computing environment220 that may be the computing environment 12 shown in FIGS. 1A-2 used tointerpret one or more gestures in a target recognition, analysis, andtracking system. The computing system environment 220 is only oneexample of a suitable computing environment and is not intended todeduct any limitation as to the scope of use or functionality of thepresently disclosed subject matter. Neither should the computingenvironment 220 be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary operating environment 220. In some embodiments the variousdepicted computing elements may include circuitry configured toinstantiate specific aspects of the present disclosure. For example, theterm circuitry used in the disclosure can include specialized hardwarecomponents configured to perform function(s) by firmware or switches. Inother examples embodiments the term circuitry can include a generalpurpose processing unit, memory, etc., configured by softwareinstructions that embody logic operable to perform function(s). Inexample embodiments where circuitry includes a combination of hardwareand software, an implementer may write source code embodying logic andthe source code can be compiled into machine readable code that can beprocessed by the general purpose processing unit. Since one skilled inthe art can appreciate that the state of the art has evolved to a pointwhere there is little difference between hardware, software, or acombination of hardware/software, the selection of hardware versussoftware to effectuate specific functions is a design choice left to animplementer. More specifically, one of skill in the art can appreciatethat a software process can be transformed into an equivalent hardwarestructure, and a hardware structure can itself be transformed into anequivalent software process. Thus, the selection of a hardwareimplementation versus a software implementation is one of design choiceand left to the implementer.

In FIG. 4, the computing environment 220 comprises a computer 241, whichtypically includes a variety of computer readable media. Computerreadable media can be any available media that can be accessed bycomputer 241 and includes both volatile and nonvolatile media, removableand non-removable media. The system memory 222 includes computer storagemedia in the form of volatile and/or nonvolatile memory such as readonly memory (ROM) 223 and random access memory (RAM) 260. A basicinput/output system 224 (BIOS), containing the basic routines that helpto transfer information between elements within computer 241, such asduring start-up, is typically stored in ROM 223. RAM 260 typicallycontains data and/or program modules that are immediately accessible toand/or presently being operated on by processing unit 259. By way ofexample, and not limitation, FIG. 4 illustrates operating system 225,application programs 226, other program modules 227, and program data228.

The computer 241 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 4 illustrates a hard disk drive 238 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 239that reads from or writes to a removable, nonvolatile magnetic disk 254,and an optical disk drive 240 that reads from or writes to a removable,nonvolatile optical disk 253 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 238 is typically connectedto the system bus 221 through a non-removable memory interface such asinterface 234, and magnetic disk drive 239 and optical disk drive 240are typically connected to the system bus 221 by a removable memoryinterface, such as interface 235.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 4, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 241. In FIG. 4, for example, hard disk drive 238 is illustratedas storing operating system 258, application programs 257, other programmodules 256, and program data 255. Note that these components can eitherbe the same as or different from operating system 225, applicationprograms 226, other program modules 227, and program data 228. Operatingsystem 258, application programs 257, other program modules 256, andprogram data 255 are given different numbers here to illustrate that, ata minimum, they are different copies. A user may enter commands andinformation into the computer 241 through input devices such as akeyboard 251 and pointing device 252, commonly referred to as a mouse,trackball or touch pad. Other input devices (not shown) may include amicrophone, joystick, game pad, satellite dish, scanner, or the like.These and other input devices are often connected to the processing unit259 through a user input interface 236 that is coupled to the systembus, but may be connected by other interface and bus structures, such asa parallel port, game port or a universal serial bus (USB). The cameras26, 28 and capture device 20 may define additional input devices for theconsole 100. A monitor 242 or other type of display device is alsoconnected to the system bus 221 via an interface, such as a videointerface 232. In addition to the monitor, computers may also includeother peripheral output devices such as speakers 244 and printer 243,which may be connected through an output peripheral interface 233.

The computer 241 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer246. The remote computer 246 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 241, although only a memory storage device 247 has beenillustrated in FIG. 4. The logical connections depicted in FIG. 2include a local area network (LAN) 245 and a wide area network (WAN)249, but may also include other networks. Such networking environmentsare commonplace in offices, enterprise-wide computer networks, intranetsand the Internet.

When used in a LAN networking environment, the computer 241 is connectedto the LAN 245 through a network interface or adapter 237. When used ina WAN networking environment, the computer 241 typically includes amodem 250 or other means for establishing communications over the WAN249, such as the Internet. The modem 250, which may be internal orexternal, may be connected to the system bus 221 via the user inputinterface 236, or other appropriate mechanism. In a networkedenvironment, program modules depicted relative to the computer 241, orportions thereof, may be stored in the remote memory storage device. Byway of example, and not limitation, FIG. 4 illustrates remoteapplication programs 248 as residing on memory device 247. It will beappreciated that the network connections shown are exemplary and othermeans of establishing a communications link between the computers may beused.

The computer readable storage medium may comprise computer readableinstructions for modifying a visual representation. The instructions maycomprise instructions for rendering the visual representation, receivingdata of a scene, wherein the data includes data representative of auser's temperament identity gesture in a physical space, and modifyingthe visual representation based on the user's temperament identitygesture, wherein the temperament identity gesture is a gesture that mapsto a control for applying attributes indicative of a temperament to theuser's visual representation.

FIG. 5A depicts an example skeletal mapping of a user that may begenerated from image data captured by the capture device 20. In thisembodiment, a variety of joints and bones are identified: each hand 502,each forearm 504, each elbow 506, each bicep 508, each shoulder 510,each hip 512, each thigh 514, each knee 516, each foreleg 518, each foot520, the head 522, the torso 524, the top 526 and bottom 528 of thespine, and the waist 530. Where more points are tracked, additionalfeatures may be identified, such as the bones and joints of the fingersor toes, or individual features of the face, such as the nose and eyes.

Through moving his body, a user may create gestures. A gesture comprisesa motion or pose by a user that may be captured as image data and parsedfor meaning. A gesture may be dynamic, comprising a motion, such asmimicking throwing a ball. A gesture may be a static pose, such asholding one's crossed forearms 504 in front of his torso 524. A gesturemay also incorporate props, such as by swinging a mock sword. A gesturemay comprise more than one body part, such as clapping the hands 502together, or a subtler motion, such as pursing one's lips.

A user's gestures may be used for input in a general computing context.For instance, various motions of the hands 502 or other body parts maycorrespond to common system wide tasks such as navigate up or down in ahierarchical list, open a file, close a file, and save a file. Forinstance, a user may hold his hand with the fingers pointing up and thepalm facing the capture device 20. He may then close his fingers towardsthe palm to make a fist, and this could be a gesture that indicates thatthe focused window in a window-based user-interface computingenvironment should be closed. Gestures may also be used in avideo-game-specific context, depending on the game. For instance, with adriving game, various motions of the hands 502 and feet 520 maycorrespond to steering a vehicle in a direction, shifting gears,accelerating, and braking. Thus, a gesture may indicate a wide varietyof motions that map to a displayed user representation, and in a widevariety of applications, such as video games, text editors, wordprocessing, data management, etc.

A user may generate a gesture that corresponds to walking or running, bywalking or running in place in the physical space. For example, the usermay alternately lift and drop each leg 512-520 to mimic walking withoutmoving. The system may parse this gesture by analyzing each hip 512 andeach thigh 514. A step may be recognized when one hip-thigh angle (asmeasured relative to a vertical line, wherein a standing leg has ahip-thigh angle of 0°, and a forward horizontally extended leg has ahip-thigh angle of 90°) exceeds a certain threshold relative to theother thigh. A walk or run may be recognized after some number ofconsecutive steps by alternating legs. The time between the two mostrecent steps may be thought of as a period. After some number of periodswhere that threshold angle is not met, the system may determine that thewalk or running gesture has ceased.

Given a “walk or run” gesture, an application may set values forparameters associated with this gesture. These parameters may includethe above threshold angle, the number of steps required to initiate awalk or run gesture, a number of periods where no step occurs to end thegesture, and a threshold period that determines whether the gesture is awalk or a run. A fast period may correspond to a run, as the user willbe moving his legs quickly, and a slower period may correspond to awalk.

A gesture may be associated with a set of default parameters at firstthat the application may override with its own parameters. In thisscenario, an application is not forced to provide parameters, but mayinstead use a set of default parameters that allow the gesture to berecognized in the absence of application-defined parameters. Informationrelated to the gesture may be stored for purposes of pre-cannedanimation.

There are a variety of outputs that may be associated with the gesture.There may be a baseline “yes or no” as to whether a gesture isoccurring. There also may be a confidence level, which corresponds tothe likelihood that the user's tracked movement corresponds to thegesture. This could be a linear scale that ranges over floating pointnumbers between 0 and 1, inclusive. Wherein an application receivingthis gesture information cannot accept false-positives as input, it mayuse only those recognized gestures that have a high confidence level,such as at least 0.95. Where an application must recognize everyinstance of the gesture, even at the cost of false-positives, it may usegestures that have at least a much lower confidence level, such as thatmerely greater than 0.2. The gesture may have an output for the timebetween the two most recent steps, and where only a first step has beenregistered, this may be set to a reserved value, such as −1 (since thetime between any two steps must be positive). The gesture may also havean output for the highest thigh angle reached during the most recentstep.

Another exemplary gesture is a “heel lift jump.” In this, a user maycreate the gesture by raising his heels off the ground, but keeping histoes planted. Alternatively, the user may jump into the air where hisfeet 520 leave the ground entirely. The system may parse the skeletonfor this gesture by analyzing the angle relation of the shoulders 510,hips 512 and knees 516 to see if they are in a position of alignmentequal to standing up straight. Then these points and upper 526 and lower528 spine points may be monitored for any upward acceleration. Asufficient combination of acceleration may trigger a jump gesture. Asufficient combination of acceleration with a particular gesture maysatisfy the parameters of a transition point.

Given this “heel lift jump” gesture, an application may set values forparameters associated with this gesture. The parameters may include theabove acceleration threshold, which determines how fast some combinationof the user's shoulders 510, hips 512 and knees 516 must move upward totrigger the gesture, as well as a maximum angle of alignment between theshoulders 510, hips 512 and knees 516 at which a jump may still betriggered. The outputs may comprise a confidence level, as well as theuser's body angle at the time of the jump.

Setting parameters for a gesture based on the particulars of theapplication that will receive the gesture are important in accuratelyidentifying gestures. Properly identifying gestures and the intent of auser greatly helps in creating a positive user experience.

An application may set values for parameters associated with varioustransition points to identify the points at which to use pre-cannedanimations. Transition points may be defined by various parameters, suchas the identification of a particular gesture, a velocity, an angle of atarget or object, or any combination thereof If a transition point isdefined at least in part by the identification of a particular gesture,then properly identifying gestures assists to increase the confidencelevel that the parameters of a transition point have been met.

Another parameter to a gesture may be a distance moved. Where a user'sgestures control the actions of a visual representation in a virtualenvironment, that avatar may be arm's length from a ball. If the userwishes to interact with the ball and grab it, this may require the userto extend his arm 502-510 to full length while making the grab gesture.In this situation, a similar grab gesture where the user only partiallyextends his arm 502-510 may not achieve the result of interacting withthe ball. Likewise, a parameter of a transition point could be theidentification of the grab gesture, where if the user only partiallyextends his arm 502-510, thereby not achieving the result of interactingwith the ball, the user's gesture also will not meet the parameters ofthe transition point.

A gesture or a portion thereof may have as a parameter a volume of spacein which it must occur. This volume of space may typically be expressedin relation to the body where a gesture comprises body movement. Forinstance, a football throwing gesture for a right-handed user may berecognized only in the volume of space no lower than the right shoulder510 a, and on the same side of the head 522 as the throwing arm 502a-310 a. It may not be necessary to define all bounds of a volume, suchas with this throwing gesture, where an outer bound away from the bodyis left undefined, and the volume extends out indefinitely, or to theedge of scene that is being monitored.

FIG. 5B provides further details of one exemplary embodiment of thegesture recognizer engine 192 of FIG. 2. As shown, the gesturerecognizer engine 190 may comprise at least one filter 519 to determinea gesture or gestures. A filter 519 comprises information defining agesture 526 (hereinafter referred to as a “gesture”), and may compriseat least one parameter 528, or metadata, for that gesture 526. Forinstance, a throw, which comprises motion of one of the hands frombehind the rear of the body to past the front of the body, may beimplemented as a gesture 526 comprising information representing themovement of one of the hands of the user from behind the rear of thebody to past the front of the body, as that movement would be capturedby the depth camera. Parameters 528 may then be set for that gesture526. Where the gesture 526 is a throw, a parameter 528 may be athreshold velocity that the hand has to reach, a distance the hand musttravel (either absolute, or relative to the size of the user as awhole), and a confidence rating by the recognizer engine 192 that thegesture 526 occurred. These parameters 528 for the gesture 526 may varybetween applications, between contexts of a single application, orwithin one context of one application over time.

Filters may be modular or interchangeable. In an embodiment, a filterhas a number of inputs, each of those inputs having a type, and a numberof outputs, each of those outputs having a type. In this situation, afirst filter may be replaced with a second filter that has the samenumber and types of inputs and outputs as the first filter withoutaltering any other aspect of the recognizer engine 190 architecture. Forinstance, there may be a first filter for driving that takes as inputskeletal data and outputs a confidence that the gesture 526 associatedwith the filter is occurring and an angle of steering. Where one wishesto substitute this first driving filter with a second drivingfilter—perhaps because the second driving filter is more efficient andrequires fewer processing resources—one may do so by simply replacingthe first filter with the second filter so long as the second filter hasthose same inputs and outputs—one input of skeletal data type, and twooutputs of confidence type and angle type.

A filter need not have a parameter 528. For instance, a “user height”filter that returns the user's height may not allow for any parametersthat may be tuned. An alternate “user height” filter may have tunableparameters—such as to whether to account for a user's footwear,hairstyle, headwear and posture in determining the user's height.

Inputs to a filter may comprise things such as joint data about a user'sjoint position, like angles formed by the bones that meet at the joint,RGB color data from the scene, and the rate of change of an aspect ofthe user. Outputs from a filter may comprise things such as theconfidence that a given gesture is being made, the speed at which agesture motion is made, and a time at which a gesture motion is made.

A context may be a cultural context, and it may be an environmentalcontext. A cultural context refers to the culture of a user using asystem. Different cultures may use similar gestures to impart markedlydifferent meanings. For instance, an American user who wishes to tellanother user to “look” or “use his eyes” may put his index finger on hishead close to the distal side of his eye. However, to an Italian user,this gesture may be interpreted as a reference to the mafia.

Similarly, there may be different contexts among different environmentsof a single application. Take a first-person shooter game that involvesoperating a motor vehicle. While the user is on foot, making a firstwith the fingers towards the ground and extending the first in front andaway from the body may represent a punching gesture. While the user isin the driving context, that same motion may represent a “gear shifting”gesture. There may also be one or more menu environments, where the usercan save his game, select among his character's equipment or performsimilar actions that do not comprise direct game-play. In thatenvironment, this same gesture may have a third meaning, such as toselect something or to advance to another screen.

The gesture recognizer engine 190 may have a base recognizer engine 517that provides functionality to a gesture filter 519. In an embodiment,the functionality that the recognizer engine 517 implements includes aninput-over-time archive that tracks recognized gestures and other input,a Hidden Markov Model implementation (where the modeled system isassumed to be a Markov process—one where a present state encapsulatesany past state information necessary to determine a future state, so noother past state information must be maintained for this purpose—withunknown parameters, and hidden parameters are determined from theobservable data), as well as other functionality required to solveparticular instances of gesture recognition.

Filters 519 are loaded and implemented on top of the base recognizerengine 517 and can utilize services provided by the engine 517 to allfilters 519. In an embodiment, the base recognizer engine 517 processesreceived data to determine whether it meets the requirements of anyfilter 519. Since these provided services, such as parsing the input,are provided once by the base recognizer engine 517 rather than by eachfilter 519, such a service need only be processed once in a period oftime as opposed to once per filter 519 for that period, so theprocessing required to determine gestures is reduced.

An application may use the filters 519 provided by the recognizer engine190 or it may provide its own filter 519, which plugs in to the baserecognizer engine 517. In an embodiment, all filters 519 have a commoninterface to enable this plug-in characteristic. Further, all filters519 may utilize parameters 528, so a single gesture tool as describedbelow may be used to debug and tune the entire filter system 519.

These parameters 528 may be tuned for an application or a context of anapplication by a gesture tool 521. In an embodiment, the gesture tool521 comprises a plurality of sliders 523, each slider 523 correspondingto a parameter 528, as well as a pictorial representation of a body 524.As a parameter 528 is adjusted with a corresponding slider 523, the body524 may demonstrate both actions that would be recognized as the gesturewith those parameters 528 and actions that would not be recognized asthe gesture with those parameters 528, identified as such. Thisvisualization of the parameters 528 of gestures provides an effectivemeans to both debug and fine tune a gesture.

FIG. 6 depicts a system 600 that may comprise a capture device 608, acomputing device 610, and a display device 612. For example, the capturedevice 608, computing device 610, and display device 612 may eachcomprise any suitable device that performs the desired functionality,such as the devices described with respect to FIGS. 1-5B. It iscontemplated that a single device may perform all of the functions insystem 600, or any combination of suitable devices may perform thedesired functions. For example, the computing device 610 may provide thefunctionality described with respect to the computing environment 12shown in FIG. 2 or the computer in FIG. 3. As shown in FIG. 2, thecomputing environment 12 may include the display device and a processor.The computing device 610 may also comprise its own camera component ormay be coupled to a device having a camera component, such as capturedevice 608.

In this example, a depth camera 608 captures a scene in a physical space601 in which a user 602 is present. The depth camera 608 processes thedepth information and/or provides the depth information to a computer,such as computer 610. The depth information can be interpreted fordisplay of a visual representation of the user 602. For example, thedepth camera 608 or, as shown, a computing device 610 to which it iscoupled, may output to a display 612.

The visual representation of a user 602 in the physical space 601 cantake any form, such as an animation, a character, an avatar, or thelike. For example, the visual representation of the target, such as auser 602, may initially be a digital lump of clay that the user 602 cansculpt into desired shapes and sizes, or a character representation,such as the monkey 604 shown on display device 612. The visualrepresentation may be a combination of the user's 602 features and ananimation or stock model. The visual representation may be a stock modelprovided with the system 600 or application. For example, the user 602may select from a variety of stock models that are provided by a gameapplication. In a baseball game application, for example, the optionsfor visually representing the user 602 may take any form, from arepresentation of a well-known baseball player to a piece of taffy or anelephant to a fanciful character or symbol, such as a cursor or handsymbol. The stock model may be modified with features of the user thatare detected by the system. The visual representation may be specific toan application, such as packaged with a program, or the visualrepresentation may be available across-applications or availablesystem-wide.

The example visual representation shown in FIG. 6, as shown on thedisplay device 612, is that of a monkey character 603. Though additionalframes of image data may be captured and displayed, the frame depictedin FIG. 6 is selected for exemplary purposes. The rate that frames ofimage data are captured and displayed may determine the level ofcontinuity of the displayed motion of the visual representation. It isalso noted that an alternate or additional visual representation maycorrespond to another target in the physical space 601, such as anotheruser or a non-human object, or the visual representation may be apartial or entirely virtual object.

The system 600 may capture information about the physical space 601,such as depth information, image information, RGB data, etc. Accordingto one embodiment, image data may include a depth image or an image froma depth camera 608 and/or RGB camera, or an image on any other detector.For example, camera 608 may process the image data and use it todetermine the shape, colors, and size of a target. Each target or objectthat matches the human pattern may be scanned to generate a model suchas a skeletal model, a flood model, a mesh human model, or the likeassociated therewith. For example, as described above, the depthinformation may be used to generate a skeletal model of the user, suchas that shown in FIG. 5A, where the system identifies the user's bodyparts such as the head and limbs. Using, for example, the depth valuesin a plurality of observed pixels that are associated with a humantarget and the extent of one or more aspects of the human target such asthe height, the width of the head, or the width of the shoulders, or thelike, the size of the human target may be determined.

The system 600 can track the movements of the user's limbs by analyzingthe captured data and translating it to the skeletal model. The system600 can then track the skeletal model and map the movement of each bodypart to a respective portion of the visual representation. For example,if the user 602 waves his or her arm, the system may capture this motionand apply it to the virtual monkey's 603 arm such that the virtualmonkey also waves its arm. Further, the system 600 may identify agesture from the user's motion by evaluating the user's position in asingle frame of capture data or over a series of frames and apply thegesture to the visual representation.

The system can use captured data, such as scanned data, image data ordepth information to detect characteristics. The detectablecharacteristics may include any characteristics related to the user orthe physical space that are detectable by the system 600. For example,detectable characteristics may include target characteristics (e.g., auser's facial features, hair color, voice analysis, etc.), gestures(i.e., gestures performed by the user and recognized by the system 600),history data (data such as user tendency data that is detected by thesystem and can be stored), application status (e.g., failure/success ina game application), or any other characteristic detectable by thesystem that may be indicative of a user's temperament or can be used todeduct a user's temperament.

The system may analyze one or more detectable characteristics to deducea user's temperament. The deduction may be based on inference orassumption or it may be based on scientific methods, such as the resultsof a study of temperaments and correlating characteristics. Thus, thededuction may be based on a simple analysis of typical characteristicsthat indicate a particular temperament, the identity of a gesture thatindicates a specific temperament, a comparison of the detectablefeatures to an in-depth analysis of psychology and the characteristicsthat correlate to various temperaments, or the like.

Target characteristics may include information that may be associatedwith the particular user 602 such as behaviors, speech patterns, facialexpressions, skeletal movements, words spoken, history data, voicerecognition information, or the like. Target characteristics maycomprise any features of the target, such as: eye size, type, and color;hair length, type, and color; skin color; clothing and clothing colors.For example, colors may be identified based on a corresponding RGBimage. Other target characteristics for a human target may include, forexample, height and/or arm length and may be obtained based on, forexample, a body scan, a skeletal model, the extent of a user 602 on apixel area or any other suitable process or data. The computing system610 may use body recognition techniques to interpret the image data andmay size and shape the visual representation of the user 602 accordingto the size, shape and depth of the user's 602 appendages.

As described, the system 600 may identify data from the physical spacethat includes an indication of the user's temperament. For example, thesystem 600 may gather information related to the user's motions, facialexpressions, body language, emotions, etc., in the physical space. Thesystem 10 may use body posture recognition techniques to assist in theidentity of the emotions or temperament of the human target 18. Forexample, the system 600 may analyze and track a skeletal model of theuser to determine how the user moves. The system 600 may track theuser's body and the motions made by the user's body, including gesturesthat control aspects of the system, such as the application, operatingsystem, or the like. The system may identify the user's body posture,facial expressions, vocal expressions and tone, directed gazes, etc. Theuser's vocal expressions may provide an indication of the user'stemperament. For example, the language used, the tone of voice, thepitch, volume, and the like may convey a sense of the user'stemperament. For example, a harsh tone may be interpreted as anger oraggression. Other tones may be tense, modal, breathy, whispery, creaky,calm, excited, happy, or any other tone. Thus, the user'scharacteristics are good indicators of the user's temperament.

The system may apply least one of the detected target characteristics ofthe user, as captured by the system 600, to the visual representation ofthe user. For example, the system may detect that the user is wearingglasses and has a red shirt on and apply glasses and system may applyglasses and a red shirt to the virtual monkey 603 which, in thisexample, is the visual representation of the user. The system mayidentify the user's facial movements, such as the movement of the user'seyebrows and/or a frowning or smiling expression. The system may detectwords said by the user and the user's tone of voice, or the user's bodyposition, etc. For example, the system may detect the right arm of aperson and have the fidelity to distinguish the upper arm, lower arm,fingers, the thumb, joints in the fingers, etc. The system may be ableto identify a color of the user's shirt that corresponds to the user'supper and lower arms and apply the color appropriately to the visualrepresentation. The system may be able to identify a ring on a finger ora tattoo on the user's hand, and based on the model of the usergenerated by the system, apply the detected target characteristics tothe visual representation to mimic the user's features in the physicalspace. The visual representation may look like the user, move like theuser, have clothes on that resemble those of the user, etc.

Certain target characteristics detected by the system and used to deducethe user's temperament may not be directly applied to the user, butmodified for display purposes. The user's characteristics may bemodified to correspond to the form of the visual representation, theapplication, the status of the application, etc. Certain characteristicsmay not map directly to the visual representation of the user where thevisual representation is a fanciful character. For example, thecharacter representation of the user, such as the monkey 603 shown ondisplay device 612, may be given body proportions, for example, that aresimilar to the user 602, but modified for the particular character. Themonkey representation 603 may be given a height that is similar to theuser 602, but the monkey's arms may be proportionately longer than theuser's arms. The movement of the monkey's 604 arms may correspond to themovement of the user's arms, as identified by the system, but the systemmay modify the animation of the monkey's arms to reflect the way amonkey's arms would move.

In the example shown in FIG. 6, the user is sitting with a head tiltedto the side, a right elbow resting on the knee, and the head beingsupported by the user's right hand. The user's facial expressions, bodyposition, words spoken, or any other detectable characteristic may beapplied to the virtual monkey 603, and modified if appropriate. Forexample, the user is frowning in the physical space. The system detectsthis facial expression and applies a frown to the monkey such that thevirtual monkey is also frowning. Further, the monkey is seated in aposition similar to the user, except modified to correspond to amonkey's body type and size in that position. Similarly, the system mayuse the user's target characteristics to deduct the user's temperament,but then apply attributes to the user's visual representation that areindicative of the temperament but that may or may not map directly tothe user's characteristics.

The system 600 may compare the detected target characteristics with alibrary of possible temperaments and determine what attributes should beapplied to the user's visual representation. For example, as describedfurther below with respect to FIGS. 7 and 8, the computer 610 may storelookup tables with a compilation of temperament information. The lookuptables may include specific or general temperament information. Thedetected characteristics may be compared to the lookup tables to deducethe temperament of the user. The analysis may include a comparison ofthe detected body position, facial expressions, vocal tone and words,gestures, history data, or the like.

FIG. 7 shows an example method of deducting a user's temperament andselecting attributes indicative of the temperament for a display of thevisual representation that corresponds to the temperament. For example,at 702, the system receives data from a physical space that includes auser. As described above, a capture device can capture data of a scene,such as the depth image of the scene and scan targets in the scene. Thecapture device may determine whether one or more targets in the scenecorrespond to a human target such as a user. Each target or object thatmatches the human body model may then be scanned to generate a skeletalmodel associated therewith. The skeletal model may then be provided tothe computing environment for tracking the skeletal model and renderinga visual representation associated with the skeletal model.

At 704, the system may render a visual representation of the user. Thevisual representation may be based on the model, for example. The visualrepresentation of a target in the physical space 601 can take any form,such as an animation, a character, an avatar, or the like. The visualrepresentation may initially be a digital lump of clay that the user 602can sculpt into desired shapes and sizes, or a character representation,such as the monkey 604. The visual representation may be directlymodeled based on the features of the user detected by the capture deviceor it may be a fanciful character having select features of the user.The visual representation may be a combination of the user's 602features and an animation or stock model.

The system may track the user and detect features of the user that areindicative of the user's temperament at 706. For example, the system maytrack a user's facial expressions and body movements to identify atemperament and then apply that temperament such that the avatarreflects the user's emotions. The system may use any detectable featuresto evaluate the user's temperament for application to the visualrepresentation. The system may analyze the detected features at 708, anddeduct a user's temperament. For example, a processor in the system maystore lookup tables or databases with temperament information. Thedetected features of the user may be compared to the features in thedatabase or lookup table that are indicative of various temperaments.For example, the lookup table may define the features that areindicative of a “sad” temperament. Such features may be a frown, tears,a low and quiet vocal tone, and arms folded across the chest. If any orall of these features of a user in the physical space are detected, theprocessor may deduct that the user is exhibiting a “sad” temperament.

The lookup tables or database, for example, may apply to applicable toan application or may be system-wide. For example, a game applicationmay define the features that indicate the various temperamentsapplicable to the game. The temperaments defined may include specificand general temperaments and may identify the temperaments comparing oneor more inputs (i.e., detected features) to the features that defineeach temperament. It is also noted that references to a lookup table ordatabase are exemplary, and it is contemplated that temperamentinformation related to the techniques disclosed herein may be accessed,stored, packaged, provided, generated, or the like, in any mannersuitable.

Alternately or in combination, the system may identify a temperamentrequest gesture from the data captured with respect to the user at 710.For example, the user may perform a gesture that requests that aparticular gesture be applied to the user's visual representation.

At 712, the system may select attributes to apply to the user's visualrepresentation that reflect the temperament deducted or identified fromthe user's gesture. The attributes applicable to a particulartemperament may be in lookup tables or a database as well. Theattributes selected may be the features of the user detected by thecapture device and/or the attributes selected may be animations thatreflect the temperament. For example, if the system deducts that theuser exhibits features indicative of a “sad” temperament, the lookuptables may indicate various animations that would reflect suchtemperament. The system may select any of these attributes and applythem to the user's visual representation.

The application of the attributes to the visual representation at 714may occur in real time. Thus, the data captured with regards to theuser's mood or emotions, along with body recognition analysis, etc., maybe performed in real time and applied to the user's visualrepresentation in real time. The user can therefore see a real timedisplay of the user's emotions or temperament.

The system may continue to track the user and any motion in the physicalspace over time at 716 and apply modifications or updates to the visualrepresentation at 718 to reflect changes in temperament. For example,the updates may be based on the changes in the user's detected featuresand history data. At any time, the capture device may identify behaviorsand mannerisms, emotions, speech patterns, or the like, of a user todetermine the user's temperaments and apply these to the user's visualrepresentation. The updates may be applied to the visual representationin real time. For example, it may be desirable that the system capturesa user's expressions and mimics over time to reflect the user'stemperament via the visual representation.

FIG. 8 depicts an example of a lookup table 800 that may be used todeduce the temperament of the user. The example temperament lookup table800 shown in FIG. 8 includes categories of detectable characteristics,such as a facial expression 802, vocal tone 804, vocal volume 806, words808, body position 810, gesture 812, application results 814, andhistory data 816. The detected features or characteristics may includeany feature in the physical space for which the system can captureinformation via the capture device, including detectable targetcharacteristics, application status, etc. The categories in the lookuptable 800 are exemplary, as any number and type of categories may bepart of the user's temperament analysis. For example, the categories mayfurther include a detected interaction with other users or objects, ananalysis of the type of clothing the user is wearing, other items on theuser's body, etc. It is contemplated that any detectable feature orcharacteristic of the user that may be captured by the system 600 insome manner that can be used in part of the analysis of the user'sattitude or temperament may be applicable.

Three examples of detected characteristics are shown in the chart 800for three users, where each of rows A, B, and C represent the detectedcharacteristics. The first portion of the table 850 represents thedetectable characteristics of the target captured in the scene. Thesecond portion of the table 860 represents other detectablecharacteristics, such as the identification of a gesture being performedby the user, the status of the application and the results of such,and/or the history data specific to the user or the application. Thelast portion of the table 870 represents the system's deduction of theuser's temperament as a result of an analysis of the availabledetectable features. As stated, the categories in table 800 are forexemplary purposes only and may be more or less inclusive of additionaldetectable characteristics.

Row A represents an example embodiment of the characteristics detectedby the system. In row A, the system detects that a first user has afacial expression including a frown, the results in the application is afailure, and history data for the first user shows a tendency for theuser to frown after failed results. An analysis of the system of thesedetected features may indicate that the temperament of the first user is“generally negative.” Possibly additional detectable features wouldprovide a more specific temperament, but with the data available, thesystem deducts the more general, generally negative temperament.

With respect to the second user, with the detectable characteristics setforth in row B, the system detects a frowning facial expression, a tersevocal tone, with quiet volume, no words, but the user's body positioncomprises a leaning back position, the head dropped to one side andsupported by one hand. The system may determine from these features thatthe user's temperament is generally negative or possibly bored, tired,angry, sad, etc. The system may further detect, with respect to thesecond user, that it is a different user's turn to play in the gameapplication, that the different user's turn has lasted for a long time,and detect, from an analysis of the user's history data, the temperamenttendencies of this user under these circumstances. With that data, thesystem may determine that the second user's temperament is not onlygenerally negative, but specifically bored or disinterested. Forexample, the system may identify the tendency of the second user, whenthe second user is not the active player in the game application, tohave facial expressions, tones, body positions, etc., that correspond toa “bored” temperament.

It is contemplated that, for example, a frowning facial expression couldcorrespond to many temperaments. The example temperaments and featuresthat indicate each of the particular temperaments shown in Table 800 areexemplary only. Each detectable characteristic may be used to narrowdown the temperament to a more specific attitude or mood, or the systemmay simply identify a general attitude, such as generally negative orpositive.

The detectable characteristics of the third user, shown in Row C,include a smiling facial expression, a happy tone that is also loud, thewords “Yeah” and “Awesome,” and a body position that includes armsraised and jumping up and down. The jumping up and down motion may alsobe indicative of a gesture applicable to the application that results ina successful game result for the third user. The comparison of thesedetectable characteristics to the user's history data may also providean indication of the likely temperament of the third user based on thisinformation. In this example, the system deducts that the user'stemperament, based on the detectable characteristics, is that of“excited.”

The system may simply map the user's actual characteristics to thevisual representation. In the example embodiment where the visualrepresentation maps directly to the user's detected features, the user'stemperament is inherently demonstrated by the visual representation asthe visual representation reflects the user's detected features.However, the visual representation may not always be a directrepresentation of the user, and so the system may modify the temperamentto correspond to the form of the visual representation. Upon a deductionof the user's temperament, the system may determine appropriateanimations to apply to the visual representation of the user to reflectthat temperament.

For example, FIG. 6 depicted the application of the user's facialexpressions, body position, etc., to the visual representation 603 ofthe user, modified to represent the corresponding features of the monkeycharacter. The monkey is frowning, but the monkey's mouth may not be adirect mapping of the user's mouth but rather, the system may apply thedetected frown to the virtual monkey's mouth the way it would appear ifa monkey were to frown. The translation of the user's temperament to theuser's visual representation may take many forms and may comprise anynumber of animations. For example, if the visual representation of auser is a “house,” the house may not be animated with facial features.Thus, the system may map the temperament to the house by translating theuser's temperament to a new form. For example, if the system detectsthat the user has a “sad” temperament, detected based on the user'sfacial expressions or body position, the system may translate this tothe house by displaying virtual windows of the virtual house to sag, andanimating the house such that it appears to puff up and then let air outthe front door, giving the appearance that the house has sighed.

A system can deduct a temperament that may be a mood or attitude of theuser based on the detectable characteristics. A temperament can includeany representation of a user's emotional response that expresses theuser's feelings or thoughts. A temperament identified may be generallypositive or negative, or it may be ambivalent. The attitude identifiedmay be more specific, such as happy, angry, frustrated, bored, sad, etc.The specificity of the attitude may depend on the library ofattitudes/emotions/moods, and the system 600 may identify a range ofattitudes of the user, from general to specific. For example, the systemmay determine from the detectable features of the user's upright bodyposition and upbeat vocal tone that the user generally has a positiveattitude. Alternately, the system may determine, more specifically, thatthe user is excited because the upright body position includes jumpingup and down, raised arms, and history data of the user indicates thatthese detectable characteristics indicate an excited temperament.Different applications may have a vaster database of both general andspecific moods and temperaments, and other applications may deductgeneral temperaments, such as generally positive or generally negative.

The greater number of detectable features may increase the fidelity ofthe system's analysis of the user's attitude. Changes in a user's bodyposture may be strong indicators of a user's temperament. A user'sposture may include the position of the user's body, the way the userstands, sits, holds his or her chest, and where the user places hisarms, legs, and feet. For example, if a user is leaning back with his orher head dropped to one side, where the head is supported by the user'shand, the system may identify the user's temperament to be bored ordisinterested. Or, for example, if a user is sitting upright with thehead erect and arms folded across the chest, with a pursed lipsexpression, the system may identify the user's temperament as one ofdisagreement, defensive, or frustrated. In general, a negativeconnotation may be reflected in the user's avatar. The system may detecta change in the user's body posture as a result of the user's tighteningof the muscles in the neck or shoulders. Sometimes a user's slouch issimply an indication that a user is relaxing or maybe has bad posture.The position of a user's head may be an indication of a user'stemperament. The system may detect a user's tensing of the jaw orfurrowing o the brow.

FIG. 9 depicts the system 600 shown in FIG. 6, where the system tracks auser's detectable features and deducts a temperament. The temperamentmay be reflected in the user's visual representation by mapping theuser's detectable features to the visual representation. The temperamentmay also be reflected by an application of animations that correspond toa particular temperament to the user's visual representation. FIG. 9depicts the user 602 at three points in time in the physical space 601,where 901 a, 901 b, and 901 c represent the physical space at the threediscrete points in time. At each point in time, the user 602 may haveshifted, changed facial expressions, performed a different motion and/ormoved body position. The system 600 may capture the target, user 602, inthe physical space 601, at each point and capture the user's detectablefeatures at each point, shown in 902 a, 902 b, and 902 c. Two examplesof the resulting display of a visual representation of the user 602 areshown on example display 912 a and example display 912 b.

As discussed above, a visual representation of a user may be anyanimation, character, avatar, or the like. The example visualrepresentations shown in FIG. 9 are an avatar 905 (shown on displaydevice 912 a) or a character 907 (shown on display device 912 b). Theavatar 905, for example, may be a close representation of the user inthe physical space, mapping to the user's body position, hair coloring,clothes, etc. A character 907, for example, may be a characterrepresentation, such as the monkey shown. The character 907 may alsohave characteristics of the user as captured by the system 600. Forexample, facial expressions, clothes, etc., may be mapped to thecharacter representation.

The system 600 may identify data from the physical space that includesan indication of the user's temperament. The system 600 may apply theuser's temperament to the visual representation by applying attributesindicative of the temperament to the user's visual representation.Further, the system 600 may identify a gesture from the user's motion byevaluating the user's position in a single frame of capture data or overa series of frames. The system 600 may use a combination of informationfrom each frame of data, from the changes in captured data betweenframes of data and over time, the gestures identified from the captureddata, and any other available information, such as voice data, toidentify a user's temperament or emotion.

In an example embodiment, the avatar 905 may be given characteristicsthat are determined from the analysis of the image data. The user 602may opt for a visual representation that is mapped to the features ofthe user 602, where the user's 602 own characteristics, physical orotherwise, are represented by the visual representation. The visualrepresentation of the user 602, also called an avatar, such as avatar905, may be initialized based on the user's 602 features, such as bodyproportions, facial features, etc. For example, the skeletal model maybe the base model for the generation of a visual representation of theuser 602, modeled after the user's 602 proportions, length, weight oflimbs, etc. Then, hair color, skin, clothing, and other detectedcharacteristics of the user 602 may be mapped to the visualrepresentation.

The mapping of the user's motion may not be a direct translation of theuser's movement, as the visual representation may be adapted to themodification. For example, the visual representation of the user may bea fanciful character without facial features. The system may reflect auser's temperament in other ways that are applicable to the form of thevisual representation. Thus, the user's motions may be translated formapping to the visual representation with some added animation toreflect the form of the visual representation. For example, in FIG. 9,the visual representation of the user shown on display device 912 b isthat of a monkey character 907. Because the visual representation 907 ofthe user 602 is not a representation of the user's own physicalstructure, the user's 602 motion and/or temperament may be translated tobe consistent with the form that the visual representation 907 takes. Inthis example, for example, the detected features and/or temperament maybe translated to be consistent with the features of a monkey 907.

The user's characteristics that may also be indicative of the user'stemperament may be mapped to the visual representation based on thesystem's analysis of detectable characteristics, thereby mimicking theuser's appearance and/or movement in the physical space. In thisexample, the system tracks the user's detectable characteristics in thephysical space at three points in time, 901 a, 901 b, and 901 c. Theuser may detect that the user in position 902 a is seated with the headleaning to one side and supported by a hand. The user 902 a may befrowning and may be making sounds or saying words that are indicative ofa bored or frustrated temperament. Thus, the system may analyze thedetectable characteristics throughout time, and deduce the user'stemperament.

In this example, the system deduces a “bored” temperament of the user.The system may deduct the user's temperament from the data captured fromthe physical space at point 901 a. The system may continue to track theuser's detectable features and the physical space at 901 b and 901 crepresent examples of the user at different points in time. The systemmay apply attributes indicative of the deduced temperament based on asingle frame of captured data, such as the captured data from the scenein the physical space 901 a, or over time as a result of multiple framesof captured data, such as captured data from all three scenes 901 a, 90b, 901 c. The system may apply attributes indicative of the temperamentdeduced based on a single frame and/or over time. The confidence in thetemperament deduced may increase based on a continued analysis of theuser's detectable characteristics. Alternately, the system may detect ordeduct a different temperament based on changes in the detectablecharacteristics.

The system, in real time, may display the detected characteristics byapplying them to the user's visual representation. Thus, as shown inFIG. 6, the visual representation 603 depicts a number of the user'sdetected characteristics (e.g., facial expression, body position, etc.).Similarly, the system may use the user's target characteristics todeduct the user's temperament, but then apply attributes to the user'svisual representation that are indicative of the temperament but thatmay or may not map directly to the user's characteristics. For example,the system may deduce, from the detected characteristics, that the userlikely has a temperament of “excited and happy.” The detectedcharacteristics that indicate this temperament may be characteristicssuch as a jumping up and down motion, yelling excitedly, a successfulactivity in a gaming application, and a smile. The system may comparethese characteristics to a database, with characteristics that indicatevarious temperaments, for example, to deduce the user's temperament. Thesystem may apply the target's characteristics directly to the visualrepresentation as these characteristics may be good examples ofattributes that are indicative of the temperament. However, the systemmay alternately, or additionally, apply attributes that are indicativeof the temperament, regardless of whether or not the applied attributesare a direct mapping of the user's characteristics. For example, if thesystem deduces a “happy and excited” temperament from the user'sdetectable features, the system may animate the user's visualrepresentation to do a dance on-screen or to animate the user jumping upinto the sky and grabbing a star. The system could apply otherattributes indicative of the temperament, such as flashing words on thedisplay device (e.g., “I am really happy,” or something humorous orsilly).

In FIG. 9, the example animation of the avatar 905, that has a number ofthe user's detectable characteristics, is of the avatar 905 standingwith a head against a wall saying, “I'm bored.” The user 602 is notperforming this action and may not be saying these words at any point ascaptured by the system, but the system may apply these attributes to theuser because they are indicative of a “bored” temperament. Similarly,display device 912 b shows an example display of the visualrepresentation, where the monkey character 907 is shown dragging itsarms and very slowly making a monkey sound, “Ooh. Ooh. Ah. Ah.” Theattributes applied to the monkey are indicative of a bored temperament.The attributes may be identified by the system based on lookup tables,for example, and may be specific to the character, such as the monkey,or the attributes could be generally applicable to many types visualrepresentations.

The avatar 905 and monkey representation 907 are two different examplevisual representations that could be displayed, and are shown on exampledisplay devices 912 a and 912 b. Each visual representation 905, 907 andapplication of attributes indicative of the user's 602 temperament maybe based on a single set of captured data, such as that captured withrespect to the physical space at time 901 a. Alternately, both exampledisplays of each visual representation 905, 907 could be a result of thesystem monitoring the user 602 over time. The user may use the capturedata over time to update the user's temperament, add more features tothe visual representation, apply attributes that are indicative of amore specific temperament, or the like.

The user 602 may perform gestures that result in an application ofattributes indicative of a particular temperament to the user's visualrepresentation. A temperament identity gesture may be a gesture that isinterpreted as a request to apply attributes indicative of a particulartemperament to the visual representation of the user. For example, thesystem's detection of a user's “bored” temperament in FIG. 9 may be aresult of the system's recognition of a user's gesture in the physicalspace that indicates a “bored” temperament. The gesture may comprise,for example, the user's body position in 902 c, where the arms arefolded across the chest. To differentiate the motion from a user'smotion simply to stand this way, he gesture may comprise a dramatic holdof the arms into position, or a slow movement of the arms to be foldedacross the chest. A gesture recognition engine, such as the gesturerecognition engine 192 described with respect to FIG. 5B, may comparethe user's motion to the gesture filters that correspond to the gesturesin a gesture library 190. The user's 602 captured motion may correspondto a temperament identity gesture 196 in the gestures library 190, forexample. Thus, the application of such attributes to a visualrepresentation may be an aspect of the operating system and/orapplication that can be controlled by or recognized from the user'sgestures.

A temperament identity gesture may or may not comprise characteristicsthat are typically associated with a particular temperament. Forexample, a gesture for a “sad” temperament may be a hand movement, wherethe hand movement is not a characteristic that a person typically makeswhen having a “sad” temperament. However, the hand movement may be agesture that the user can perform to direct the system to applyattributes indicative of a “sad” temperament to the visualrepresentation. The user can therefore control the temperament of theuser's visual representation by performing gestures in the physicalspace. A user may intentionally or unintentionally perform a gesturethat corresponds to a temperament. For example, a gesture for a user'shands folded across his or her chest may be a gesture recognized as atemperament of frustration and the user may simply be conducting themotion that corresponds to the gesture because the user is feelingfrustrated.

The system's recognition of a gesture that indicates the user isfrustrated, along with a user's expression, such as a frown, may resultin a visual representation that reflects a frustrated temperament.Alternately, the user may intentionally perform a gesture in thephysical space to cause a particular temperament to be applied to theuser's visual representation. For example, the user may have just won agame or did something successful in an application. A gesture for a“happy” temperament may comprise a user's jumping up and down with armsraised motion. The user may perform the “happy” temperament gesturecausing the system to apply the target characteristics and/or any numberof “happy” attributes to the user's visual representation. For example,as described above, the user's visual representation may do a cartwheel,or perform a dance, or any other activity that the system associateswith an expression of the temperament of happiness. Thus, while thegestures in the virtual space may act as controls of an application suchas an electronic game, they may also correspond to a request by the userfor the system to reflect a particular temperament on the user's visualrepresentation.

The system 600 may update the user's temperament in the visualrepresentation of the user by monitoring the detectable characteristics.The system 600 may use a combination of information from each frame ofdata, such as that captured from the user at points 901 a, 901 b, 901 c,from the changes in captured data between frames of data and over time,the gestures identified from the captured data, the targetcharacteristics and changes in time of the target's characteristics, andany other available information, such as facial expressions, bodyposture, voice data, etc., to identify and update a temperament as it isreflected by the visual representation of the user.

The target characteristics associated with a user in the physical spacemay become part of a profile. The profile may be specific to aparticular physical space or a user, for example. Avatar data, includingfeatures of the user, may become part of the user's profile. A profilemay be accessed upon entry of a user into a capture scene. If a profilematches a user based on a password, selection by the user, body size,voice recognition or the like, then the profile may be used in thedetermination of the user's visual representation.

History data for a user may be monitored, storing information to theuser's profile. For example, the system may detect features specific tothe user, such as the user's behaviors, speech patterns, emotions,sounds, or the like. The system may apply those features to the user'svisual representation when applying a temperament to the visualrepresentation. For example, if the system identifies the user'stemperament and selects an attribute that comprises speech to reflectthe temperament, the visual representation's voice may be patterned fromthe user's speech patterns or may even be a recording of the user's ownvoice.

User specific information may also include tendencies in modes of playby one or more users. For example, if a user tends to behave or react ina certain manner, the system may track the user's tendencies to moreaccurately deduct the user's temperament. For example, if the systemdetects body positions of the user that are indicative of “angry”temperaments, and the user tends to behave in a similar manner each timethe user fails in the application (such as a game), the system may trackthis information. Thus, the system can begin to track the user'stendencies and use that information to more accurately estimate theuser's temperament.

It should be understood that the configurations and/or approachesdescribed herein are exemplary in nature, and that these specificembodiments or examples are not to be considered limiting. The specificroutines or methods described herein may represent one or more of anynumber of processing strategies. As such, various acts illustrated maybe performed in the sequence illustrated, in other sequences, inparallel, or the like. Likewise, the order of the above-describedprocesses may be changed.

Furthermore, while the present disclosure has been described inconnection with the particular aspects, as illustrated in the variousfigures, it is understood that other similar aspects may be used ormodifications and additions may be made to the described aspects forperforming the same function of the present disclosure without deviatingtherefrom. The subject matter of the present disclosure includes allnovel and non-obvious combinations and sub-combinations of the variousprocesses, systems and configurations, and other features, functions,acts, and/or properties disclosed herein, as well as any and allequivalents thereof Thus, the methods and apparatus of the disclosedembodiments, or certain aspects or portions thereof, may take the formof program code (i.e., instructions) embodied in tangible media, such asfloppy diskettes, CD-ROMs, hard drives, or any other machine-readablestorage medium. When the program code is loaded into and executed by amachine, such as a computer, the machine becomes an apparatus configuredfor practicing the disclosed embodiments.

In addition to the specific implementations explicitly set forth herein,other aspects and implementations will be apparent to those skilled inthe art from consideration of the specification disclosed herein.Therefore, the present disclosure should not be limited to any singleaspect, but rather construed in breadth and scope in accordance with theappended claims. For example, the various procedures described hereinmay be implemented with hardware or software, or a combination of both.

1. A method for applying attributes indicative of a user's temperamentto a visual representation, the method comprising: rendering the visualrepresentation of a user; receiving data of a physical space, whereinthe data is representative of the user in the physical space; analyzingat least one detectable characteristic to deduct the user's temperament;and applying attributes indicative of the user's temperament to thevisual representation.
 2. The method of claim 1, wherein applyingattributes indicative of the user's temperament to the visualrepresentation is performed in real time with respect to the receipt ofthe data of the physical space.
 3. The method of claim 1, wherein thevisual representation is at least one of an avatar, a character, acursor, or a stock model.
 4. The method of claim 1, wherein the at leastone detectable characteristic comprise at least one of a user'scharacteristics, a user's physical features, a user's behavior, a user'sspeech pattern, a user's voice, a gesture, history data, or anapplication status.
 5. The method of claim 1, wherein the data isrepresentative of at least one of a user's characteristics in thephysical space.
 6. The method of claim 1, further comprising applying atleast one of a user's characteristics to the visual representation. 7.The method of claim 1, wherein receiving data of the physical spacecomprises receiving data via a capture device.
 8. The method of claim 1,wherein analyzing detectable characteristics to deduct the user'stemperament comprises a comparison of at least one of the detectablecharacteristics to a table that correlates characteristics to aparticular temperament.
 9. The method of claim 1, wherein the user'stemperament comprises at least one of generally negative, generallypositive, ambivalent, bored, happy, sad, frustrated, excited, or angry.10. The method of claim 1, further comprising: tracking changes to theat least one detectable characteristic to deduct changes to the user'stemperament; and applying updates to the attributes indicative of theuser's temperament to correspond to the deducted changes in the user'stemperament.
 11. The method of claim 1, further comprising selectingattributes indicative of the user's temperament from a plurality ofattributes that correspond to the user's temperament.
 12. A system forapplying attributes indicative of a user's temperament to a visualrepresentation, the system comprising: a camera component, wherein thecamera component receives data of a scene, wherein the data isrepresentative of a user in a physical space; and a processor, whereinthe processor executes computer executable instructions, and wherein thecomputer executable instructions comprise instructions for: renderingthe visual representation of the user; analyzing at least one detectablecharacteristic to deduct the user's temperament; and applying attributesindicative of the user's temperament to the visual representation. 13.The system of claim 12, wherein applying attributes indicative of theuser's temperament to the visual representation is performed in realtime with respect to the receipt of the data of the physical space. 14.The system of claim 12, further comprising a memory that stores a tablethat provides characteristics that correlate to a particulartemperament.
 15. A method for applying attributes indicative of atemperament to a visual representation, the method comprising: renderingthe visual representation of a user; receiving data of a physical space,wherein the data is representative of a temperament identity gesture;and applying attributes indicative of the temperament associated withthe temperament identity gesture to the visual representation;
 16. Themethod of claim 15, wherein applying attributes indicative of thetemperament to the visual representation is performed in real time withrespect to the receipt of the data of the physical space.
 17. The methodof claim 15, wherein the visual representation is at least one of anavatar, a character, a cursor, or a stock model.
 18. The method of claim15, further comprising applying at least one of a user's characteristicsto the visual representation, wherein the data further comprises datarepresentative of the user's characteristics.
 19. The method of claim15, wherein receiving data of the physical space comprises receivingdata via a capture device.
 20. The method of claim 15, wherein thetemperament comprises at least one of generally negative, generallypositive, ambivalent, bored, happy, sad, frustrated, excited, or angry.21. The method of claim 15, further comprising: providing a filterrepresenting the temperament identity gesture, the filter comprisingbase information about the temperament identity gesture; and applyingthe filter to the data and determining an output from the baseinformation about the temperament identity gesture.
 22. The method ofclaim 15, further comprising selecting attributes indicative of thetemperament from a plurality of attributes that correspond to the user'stemperament.